Can simple be useful and reliable? Using ecological indicators to represent and compare the states of marine ecosystems
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Shin, Y-J., Bundy, A., Shannon, L. J., Simier, M., Coll, M., Fulton, E. A., Link, J. S., Jouffre, D., Ojaveer, H., Mackinson, S., Heymans, J. J., and Raid, T. 2010. Can simple be useful and reliable? Using ecological indicators to represent and compare the states of marine ecosystems. – ICES Journal of Marine Science, 67: 717–731. Within the IndiSeas WG, the evaluation of exploited marine ecosystems has several steps, from simple binary categorization of ecosystems to a more-complex attempt to rank them and to evaluate their status using decision-tree analyses. With the intention of communicating scientific knowledge to the public and stakeholders, focus is on evaluating and comparing the status of exploited marine ecosystems using a set of six ecological indicators and a simple and transparent graphic representation of ecosystem state (pie charts). A question that arose was whether it was acceptable to compare different types of marine ecosystems using a generic set of indicators. To this end, an attempt is made to provide reference levels to which ecosystems can be objectively compared. Unacceptable thresholds for each indicator are determined based on ecological expertise derived from a questionnaire distributed to a group of scientific experts. Analysis of the questionnaires revealed no significant difference in the thresholds provided for different ecosystem types, suggesting that it was reasonable to compare states directly across different types of ecosystem using the set of indicators selected.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it